best available modeling approaches, and make significant progress towards new analytical and predictive capabilities. The time is ripe to envision, plan for, and invest in the next generation of land-change models for an increasingly interdisciplinary scientific enterprise that takes advantage of the best available knowledge, data and computing resources.

If appropriately planned and executed, the next generation of models can be increasingly process based, link processes in social and natural systems from the parcel scale to regional and global scales and make use of better methods for process validation, in order to enhance both their predictive skill and their utility for policy analyses. New LCMs can also be routinely used, appropriately and with greater confidence, for a wider range of scientific and policy purposes, supporting better understanding of land systems, the effects of economic and social processes on their dynamics, and their effects on important environmental and social outcomes. Taking advantage of a wider range of Earth observation data types to enhance their spatial and temporal detail and the categories of information they represent, future LCMs can integrate these with data on the human attitudes, preferences, and behaviors related to land change, both from traditional and a growing number of novel sources for social data. Highly interconnected data systems, well-documented model and software code, and a well functioning community of land-change modelers can support the scientific enterprise to advance these goals.

Near-term intellectual and resource investments (three to six years) in the science of and infrastructure to support advancements in LCMs could help achieve these goals. This report outlines a number of specific areas that are ripe for advancement. Such investments have the potential to move forward our understanding of, ability to predict, and tools for analyzing policy related to key environmental sustainability challenges.

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